Artificial intelligence in wellbeing services counties: management and experts’ perspectives on opportunities, challenges and AI readiness

Authors

• Marketta Niemelä Nordic Healthcare Group Oy, Espoo; Faculty of Medicine and Health Technology, Tampere University, Tampere https://orcid.org/0000-0002-8370-9626
• Tommi Kemppainen Nordic Healthcare Group Oy, Espoo
• Jenny Vuollet DigiFinland Oy, Helsinki

DOI: https://doi.org/10.23996/fjhw.155471

Keywords:

artificial intelligence, wellbeing services counties, digitalisation, healthcare, implementation, interview study

Abstract

Artificial intelligence (AI) can be used to enhance healthcare efficiency and quality. New generative AI (GenAI) and large language models (LLM) offer novel opportunities for AI applications. This study examines management and expert perceptions of AI implementation opportunities and challenges in wellbeing services counties (WSCs), which are the responsible providers of healthcare and social welfare services in their region in Finland.
A qualitative interview study was conducted in two phases from Nov 2023 to Feb 2024. First, 28 participants were interviewed semi-structurally. Thematic analysis was used to identify potential AI use cases, main use contexts, and related benefits and challenges. Second, 16 participants (14 new persons and two already interviewed) validated the results in four group interviews and prioritised the use contexts by their potential for WSCs. The framework of Roppelt and colleagues was used to analyse the AI readiness of WSCs.
Six AI use contexts were identified and prioritised: 1. Clinical healthcare, 2. Patient interaction and self-care, 3. Support services, 4. Management, 5. Preventive healthcare, 6. Social welfare services. AI readiness should be increased by the government by supporting organisational collaboration, experience sharing and regulatory interpretation. Healthcare organisations need to improve AI competence and skills at all levels. Regulation and WSC culture not supporting experimentation were identified as main challenges for broader AI implementation.
AI particularly GenAI, is seen as a promising technology to address workload, financial, and service demand challenges in WSCs. Challenges can be mitigated through focused collaboration and actions within and between stakeholder organisations. AI implementation research in healthcare should consider the rapid development of AI, including increasingly human-like behaviour and integration into physical robots.